Journal articles: 'Agriculture Linear programming. Agriculture Terrains'

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Andreea, Ion Raluca, and Turek Rahoveanu Adrian. "Linear Programming in Agriculture." International Journal of Sustainable Economies Management 1, no. 1 (January 2012): 51–60. http://dx.doi.org/10.4018/ijsem.2012010105.

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In agriculture, the production structure of farms can be highly diversified to reduce risk and uncertainty related to unsealing the products. To determine the optimal structure of crops, different methods which take into account the income and expenditure of crops per hectare are used. As a result, the area of each crop is identified, so that, in combining them to derive maximum profit level. In this paper, linear programming method is used for optimizing profit, investigating whether, after applying the econometric model, the profit increased or not. The results show that profit rose to 143% and costs reduced to 81%.

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Lone, MA, MS Puktha, and SA Mir. "Fuzzy linear mathematical programming in agriculture." BIBECHANA 13 (December 3, 2015): 72–76. http://dx.doi.org/10.3126/bibechana.v13i0.13363.

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In this paper we present a Fuzzy linear Mathematical programming approach for optimal allocation of land under cultivation. Fuzzy Mathematical programming approach is more realistic and flexible optimal solution for the agricultural land cultivation problem. In this study we have discussed how to deal with decision making problems that are described by Fuzzy linear programming (Flp) models and formulated with the elements of uncertainty. This form of approximation can be convenient and sufficient for making good decisions. BIBECHANA 13 (2016) 72-76

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Butterworth, Keith. "Practical Application of Linear/Integer Programming in Agriculture." Journal of the Operational Research Society 36, no. 2 (February 1985): 99. http://dx.doi.org/10.2307/2582501.

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Butterworth, Keith. "Practical Application of Linear/Integer Programming in Agriculture." Journal of the Operational Research Society 36, no. 2 (February 1985): 99–107. http://dx.doi.org/10.1057/jors.1985.22.

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HOWES, RICHARD. "A TEST OF A LINEAR PROGRAMMING MODEL OF AGRICULTURE." Papers in Regional Science 19, no. 1 (January 14, 2005): 123–40. http://dx.doi.org/10.1111/j.1435-5597.1967.tb01374.x.

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Ward, James D., Peter J. Ward, Evangeline Mantzioris, and Christopher Saint. "Optimising diet decisions and urban agriculture using linear programming." Food Security 6, no. 5 (August 27, 2014): 701–18. http://dx.doi.org/10.1007/s12571-014-0374-0.

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Prišenk, Jernej, Jernej Turk, Črtomir Rozman, Andreja Borec, Magdalena Zrakić, and Karmen Pažek. "Advantages of combining linear programming and weighted goal programming for agriculture application." Operational Research 14, no. 2 (June 25, 2014): 253–60. http://dx.doi.org/10.1007/s12351-014-0159-4.

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Janová, Jitka, and Pavla Ambrožová. "Optimization of production planning in Czech agricultural co-operative via linear programming." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 57, no. 6 (2009): 99–104. http://dx.doi.org/10.11118/actaun200957060099.

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The production planning is one of the key managerial decisions in agricultural business, which must be done periodically every year. Correct decision must cover the agriculture demands of planting the crops such as crop rotation restrictions or water resource scarcity, while the decision maker aims to plan the crop design in most profitable way in sense of maximizing the total profit from the crop yield. This decision problem represents the optimization of crop design and can be treated by the methods of linear programming which begun to be extensively used in agriculture production planning in USA during 50’s. There is ongoing research of mathematical programming applications in agriculture worldwide, but the results are not easily transferable to other localities due to the specific local restrictions in each country. In Czech Republic the farmers use for production planning mainly their expert knowledge and past experience. However, the mathematical programming approach enables find the true optimal solution of the problem, which especially in the problems with a great number of constraints is not easy to find intuitively. One of the possible barriers for using the general decision support systems (which are based on mathematical programming methods) for agriculture production planning in Czech Republic is its expensiveness. The small farmer can not afford to buy the expensive software or to employ a mathematical programming specialist. The aim of this paper is to present a user friendly linear programming model of the typical agricultural production planning problem in Czech Republic which can be solved via software tools commonly available in any farm (e.g. EXCEL). The linear programming model covering the restrictions on total costs, crop rotation, thresholds for the total area sowed by particular crops, total amount of manure and the need of feed crops is developed. The model is applied in real-world problem of Czech agriculture cooperative and the results of its solution are compared to the real decision made. The applicability of the model in every day agriculture managerial practice in Czech Republic is discussed and its possible enlargement is mentioned.

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Novkovic, Nebojsa, Sandor Somodji, and Milenko Matkovic. "Selection of agricultural land for multifunctional agriculture." Applied Studies in Agribusiness and Commerce 4, no. 1-2 (July 30, 2010): 49–52. http://dx.doi.org/10.19041/apstract/2010/1-2/6.

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The modern concept of rural development implies the use of agricultural resources, primarily agricultural land, for other (non-agricultural) activities besides its agricultural purpose. The integral aim of this concept of rural development is the maximization of economic results, besides the sustainable development of rural areas, environmental protection and the production of strategic (staple) agricultural products. The objective of this paper is to define the general, theoretical, quantitative model for the determination of the size and quality of agricultural land which, considering the above-mentioned demands (criteria), is optimal for the utilization in agricultural production in certain regions. The remaining agricultural land would be available for the non-agricultural purposes. The economic optimal model for the selection of agricultural land in the traditional agriculture is the model of linear programming. The criteria of the land selection for traditional agriculture are the economic effectiveness (measured by net income or by gross national product) and the economic efficiency (measured by the production economy). The maximum economic effectiveness is determined by the standard method of linear programming and the maximum economy by the method of broken linear programming. The solution of compromise can be determined by multi-criteria programming, based on the minimum differences. The limitation groups in the mentioned variations of the model are: limitations of production quotas of agricultural products, minimum quantities of staple agricultural products, limitations of processing plants in a region (minimum and maximum), limitation of crop rotation, limitations of the needs in animal husbandry for bulky for age and limitations of agricultural land according to various types of utilization. By quantitative defining of the structure and size of agricultural land for traditional agriculture, “the surplus” and structure of agricultural land available for non-agricultural purposes is automatically determined.

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Lone, M. A., S. A. Mir, and M. S. Wani. "An Integer solution in Intuitionistic Transportation Problem with Application in Agriculture." Oriental journal of computer science and technology 10, no. 1 (March 27, 2017): 18–23. http://dx.doi.org/10.13005/ojcst/10.01.03.

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In this paper, we investigate a Transportation problem which is a special kind of linear programming in which profits; supply and demands are considered as Intuitionistic triangular fuzzy numbers. The crisp values of these Intuitionistic triangular fuzzy numbers are obtained by defuzzifying them and the problem is formulated into linear programming problem. The solution of the formulated problem is obtained through LINGO software. If the obtained solution is non-integer then Branch and Bound method can be used to obtain an integer solution.

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Lee, John G., Ronald D. Lacewell, Teofilo Ozuna, and Lonnie L. Jones. "Regional Impact of Urban Water Use on Irrigated Agriculture." Journal of Agricultural and Applied Economics 19, no. 2 (December 1987): 43–51. http://dx.doi.org/10.1017/s0081305200025310.

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AbstractLinear programming and regional input-output models were applied to estimate the impacts of increased pumping costs for irrigated agriculture due to groundwater depletion principally caused by the expanding urban area of San Antonio, Texas. A biophysical simulator was used to estimate linear programming coefficients of crop yield by irrigation level and timing. The results indicate significant local (county) economic impacts from groundwater mining but insignificant regional impacts. A major improvement in irrigation efficiency would be required to offset the increased pumping costs and reduced water availability associated with increased lifts due to urban expansion.

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Hu, Chang, Hui Li Yang, and Dang Sheng Li. "The Optimal Design of Saving Water on Kaifeng Agriculture Irrigated Area." Advanced Materials Research 726-731 (August 2013): 3100–3104. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.3100.

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The agricultural irrigation water of Kaifeng city is mainly supplied by the Yellow River and the local underground water. According to conditions of the irrigation area water supply and groundwater reduction for many years, the paper puts forward the optimal allocation and the supplying water programs on using combination of surface water and groundwater. By using variable one-dimensional search technology, it will express nonlinearity function is approximated by piecewise linear function so as to set up the mathematical model of controlled object, so the nonlinear programming problem will be turned into linear programming problem. Thus choose different decision variables and different parameters to use computing in order to get to approach the optimal allocation of water resources.

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Borges Júnior, João C. F., Paulo A. Ferreira, Camilo L. T. Andrade, and Bettina Hedden-Dunkhorst. "Computational modeling for irrigated agriculture planning. Part I: general description and linear programming." Engenharia Agrícola 28, no. 3 (September 2008): 471–82. http://dx.doi.org/10.1590/s0100-69162008000300008.

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Linear programming models are effective tools to support initial or periodic planning of agricultural enterprises, requiring, however, technical coefficients that can be determined using computer simulation models. This paper, presented in two parts, deals with the development, application and tests of a methodology and of a computational modeling tool to support planning of irrigated agriculture activities. Part I aimed at the development and application, including sensitivity analysis, of a multiyear linear programming model to optimize the financial return and water use, at farm level for Jaíba irrigation scheme, Minas Gerais State, Brazil, using data on crop irrigation requirement and yield, obtained from previous simulation with MCID model. The linear programming model outputted a crop pattern to which a maximum total net present value of R$ 372,723.00 for the four years period, was obtained. Constraints on monthly water availability, labor, land and production were critical in the optimal solution. In relation to the water use optimization, it was verified that an expressive reductions on the irrigation requirements may be achieved by small reductions on the maximum total net present value.

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Brožová, H., T. Šubrt, and J. Bartoška. "Knowledge maps in agriculture and rural development." Agricultural Economics (Zemědělská ekonomika) 54, No. 11 (December 2, 2008): 546–52. http://dx.doi.org/10.17221/263-agricecon.

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The possibility of knowledge maps use in the decision-making process in agriculture and rural development is discussed in this paper. Each knowledge map presents a visualization of knowledge using different tools, where a mathematical model can be applied as one of them. The hierarchical structure of a knowledge map conforms to the general structure of a mathematical model. The mathematical model, when successfully solved and correctly read, is a knowledge map in itself. The parallels exist also between the creation process of a mathematical model and of a knowledge map. In general, every phase of a system approach can lead to a special knowledge map. The following paper explains this process and demonstrates it on the farm production structure optimisation problem solved by using a linear programming model.

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Ward, James David. "Can urban agriculture usefully improve food resilience? Insights from a linear programming approach." Journal of Environmental Studies and Sciences 5, no. 4 (July 23, 2015): 699–711. http://dx.doi.org/10.1007/s13412-015-0306-0.

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Tóth, Orsolya, and István Takács. "Farm Structure And Efficiency In The Hungarian Agriculture." Visegrad Journal on Bioeconomy and Sustainable Development 4, no. 2 (October 1, 2015): 51–56. http://dx.doi.org/10.1515/vjbsd-2015-0012.

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Abstract It has long been the subject of empirical researches to examine the technical efficiency on farm (micro) level. Two main methods are most often used in the empirical literature: the non-parametric Data Envelopment Analysis (DEA) based on linear programming, and the Stochastic Frontier Analysis (SFA) introduced by Aigner, Lovell and Schmidt (1977). The present study aimed to investigate the technical efficiency of farms involved in agricultural activities in Hungary using the DEA-method and the data from the Hungarian FADN database. The technical efficiency was examined based on legal forms, farm size categories and the type of farming between 2001 and 2013.

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Borges Júnior, João C. F., Paulo A. Ferreira, Camilo L. T. Andrade, and Bettina Hedden-Dunkhorst. "Computational modeling for irrigated agriculture planning. Part II: risk analysis." Engenharia Agrícola 28, no. 3 (September 2008): 483–93. http://dx.doi.org/10.1590/s0100-69162008000300009.

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Techniques of evaluation of risks coming from inherent uncertainties to the agricultural activity should accompany planning studies. The risk analysis should be carried out by risk simulation using techniques as the Monte Carlo method. This study was carried out to develop a computer program so-called P-RISCO for the application of risky simulations on linear programming models, to apply to a case study, as well to test the results comparatively to the @RISK program. In the risk analysis it was observed that the average of the output variable total net present value, U, was considerably lower than the maximum U value obtained from the linear programming model. It was also verified that the enterprise will be front to expressive risk of shortage of water in the month of April, what doesn't happen for the cropping pattern obtained by the minimization of the irrigation requirement in the months of April in the four years. The scenario analysis indicated that the sale price of the passion fruit crop exercises expressive influence on the financial performance of the enterprise. In the comparative analysis it was verified the equivalence of P-RISCO and @RISK programs in the execution of the risk simulation for the considered scenario.

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Hang, Sheng, Jing Li, Xiangbo Xu, Yun Lyu, Yang Li, Huarui Gong, Yan Xu, and Zhu Ouyang. "An Optimization Scheme of Balancing GHG Emission and Income in Circular Agriculture System." Sustainability 13, no. 13 (June 25, 2021): 7154. http://dx.doi.org/10.3390/su13137154.

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With the rapid development of circular agriculture in China, balancing agricultural income and environmental impact by adjusting the structure and scale of circular agriculture is becoming increasingly important. Agriculture is a major source of greenhouse gas and income earned from agriculture drives sustainable agricultural development. This paper built a multi-objective linear programming model based on greenhouse gas emission and agricultural product income and then optimized the structure and scale of circular agriculture using Beiqiu Farm as a case study. Results showed that greenhouse gas emission was mainly from manure management in livestock industry. While the agriculture income increased by 64% after optimization, GHG emission increased by only 12.3%. The optimization made full use of straw, manure and fodder, but also minimized soil nitrogen loss. The results laid a generalized guide for adjusting the structure and scale of the planting and raising industry. Measures for optimizing the management of manure were critical in achieving low agricultural carbon emissions in future agricultural development efforts.

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Janová, Jitka. "The dynamic programming approach to long term production planning in agriculture." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 59, no. 2 (2011): 129–36. http://dx.doi.org/10.11118/actaun201159020129.

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The production planning in agriculture is one of the most important decision problems of the farmer. Although some decision support tools based mainly on linear programming and addressed to agriculture authorities were presented, their direct application by a farmer is not possible. This is mainly due to the local character of the models developed for particular agricultural conditions and also due to the complexness of underlying mathematical programming models.This paper aims to develop dynamic programming model for the long run crop plan optimization covering the typical conditions of Czech farms, which could serve as a platform for further enlargements and changes according to needs and conditions of particular farm. The dynamic programming algorithm is developed in detail for model case of four areas to be planted by four crops each year. The possibility of covering different constraints by generating the state space is discussed, and the generating procedure for crop rotation rules is shown. The goal function reflects the farmers objective of profit maximization and it is defined with respect to harvests’ randomness. The case study is solved for the data from South Moravian agriculture cooperative and the optimal solution is presented and discussed.

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Viaggi, Davide, Fabio Bartolini, and Meri Raggi. "Combining linear programming and principal–agent models: An example from environmental regulation in agriculture." Environmental Modelling & Software 24, no. 6 (June 2009): 703–10. http://dx.doi.org/10.1016/j.envsoft.2008.10.014.

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Difallah, Wafa, Khelifa Benahmed, Belkacem Draoui, and Fateh Bounaama. "Linear Optimization Model for Efficient Use of Irrigation Water." International Journal of Agronomy 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/5353648.

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The implementation of innovative and efficient irrigation techniques is among the greatest challenges facing agriculture. In this regard, a linear programming model is presented in order to optimize water use. The idea behind this model is to assess the effectiveness or ineffectiveness of precipitation to determine the amount of irrigation water required to optimize water use. To achieve this idea, the “knapsack” problem decisional form was used, and the combination of the linear programming and the above-mentioned form proved satisfactory. Field experiments were conducted in Algeria. Based on calculated budgets a model using linear programming was developed. A comparison between the model results and the field findings suggests that the model could reduce water consumption by 28.5%.

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Namitulina, Anzhela, Viktor Gorlov, Irina Soklakova, Elena Kuzmina, and Diana Ermilina. "Socio-economic factors in stimulating agriculture in a crisis." E3S Web of Conferences 254 (2021): 10004. http://dx.doi.org/10.1051/e3sconf/202125410004.

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Agriculture faces a series of challenges, i.e. guaranteeing national food security, increasing farmer’s income and reducing the adverse effects on environment and human health associated with the use of fertilizers and biocides. At the same time, the availability of resources (e.g. agricultural land) decreases. The objective of this study in this article is to operationalize a methodology to assess the effectiveness of new crop and livestock technologies in attaining rural development goals. Cropping systems, quantified in terms of inputs and outputs, are used as the smallest unit of analysis in this study. A land use model, based on linear programming techniques, is used to assess the contribution of alternative cropping systems to rural development goals. Results of this study contribute to the formulation of agricultural policies and a research agenda aiming at stimulating rural development.

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NGUEMA, ABIGAIL, GEORGE W. NORTON, JEFFREY ALWANG, DANIEL B. TAYLOR, VICTOR BARRERA, and MICHAEL BERTELSEN. "FARM-LEVEL ECONOMIC IMPACTS OF CONSERVATION AGRICULTURE IN ECUADOR." Experimental Agriculture 49, no. 1 (December 12, 2012): 134–47. http://dx.doi.org/10.1017/s0014479712001044.

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SUMMARYFarm households in the Andean region of South America face serious livelihood challenges, including a poor natural resource base and declining agricultural yields. Conservation agriculture has been identified as a potential solution to environmental degradation and the associated poverty and food insecurity in the region. This study analyses the potential economic impact of conservation agriculture in two sub-watersheds in central Ecuador utilizing a linear programming model and data from experiments in farmer fields. The model found that specific cover crops, crop rotations and reduced tillage designed to reduce soil erosion and increase soil organic matter can lead to increased incomes for farm households in a time period of as short as two years. It appears that conservation agriculture practices have the potential to improve the livelihoods of the rural poor in Ecuador because conservation agriculture activities entered the revenue-maximizing model solution for both sub-watersheds.

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Zahedi, Zahedi, and I. Wayan Aditya Eka Putera. "Program Aplikasi Optimalisasi Perencanaan Produksi dengan Metode Goal Programming (Kasus CV. G)." ComTech: Computer, Mathematics and Engineering Applications 1, no. 1 (June 1, 2010): 100. http://dx.doi.org/10.21512/comtech.v1i1.2176.

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Indonesia today is still a State agrarian. Thus agriculture in Indonesia always get more attention by the government. Many government programs are rolled out to support the agricultural development of Indonesia, and one of them is the fertilizer subsidy to farmers Indonesia. Fertilizer itself is very useful to nourish the soil and provide vitamins to the plants, thus increasing the amount of production generated. Therefore it is necessary fertilizer for agriculture in Indonesia. CV. G company is one of the companies that produce fertilizer. Fertilizer produced by this company is an organic fertilizer and inorganic fertilizer. Problems faced by these companies are in planning the production of fertilizer produced. Companies want to optimize the amount of production of each fertilizer, maximize revenues, minimize production costs, and simultaneously optimize the working hours of employees. To meet these objectives, this research created program package using goal programming methods. Goal programming method can provide an effective solution / equilibrium toward the goals set, and the calculation will be assisted by using the Simplex method that has been modified. This method is an extension of linear programming, linear programming which can only solve problems with a single goal while the goal programming to solve problems with multiple objectives.

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Torres, Marcelo de O., Marco Maneta, Richard Howitt, Stephen A. Vosti, Wesley W. Wallender, Luís H. Bassoi, and Lineu N. Rodrigues. "Economic impacts of regional water scarcity in the São Francisco River Basin, Brazil: an application of a linked hydro-economic model." Environment and Development Economics 17, no. 2 (November 8, 2011): 227–48. http://dx.doi.org/10.1017/s1355770x11000362.

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AbstractThis paper presents a linked hydro-economic model and uses it to examine the regional effects of water use regulations and product price changes on the agriculture of the São Francisco River Basin, Brazil. The effects of weather on surface water availability are explicitly addressed using the hydrological model MIKE-Basin. Farmers’ adjustments to changes in precipitation, surface water availability, and other factors are quantified using an economic model based on non-linear programming techniques. The models are externally linked. Results show that regional impacts, at the sub-basin level, vary depending on the location of each sub-basin relative to river flows. The effects of water use regulations and of exogenous price shocks on agriculture depend on weather, location, product mix and production technology. Implications of these results for policies designed to manage agriculture and water use are discussed.

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Fotio Tiotsop, Lohic, Antonio Servetti, and Enrico Masala. "An integer linear programming model for efficient scheduling of UGV tasks in precision agriculture under human supervision." Computers & Operations Research 114 (February 2020): 104826. http://dx.doi.org/10.1016/j.cor.2019.104826.

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Swinton, Scott M., and David S. Clark. "Farm-Level Evaluation of Alternative Policy Approaches to Reduce Nitrate Leaching from Midwest Agriculture." Agricultural and Resource Economics Review 23, no. 1 (April 1994): 66–74. http://dx.doi.org/10.1017/s1068280500000423.

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Policies to reduce nitrate leaching are evaluated using a mixed integer linear programming model of a representative Michigan cash grain farm. At spring 1993 prices, elimination of the current deficiency payment program is found to be more efficient at reducing leaching than a nitrogen input tax, a tax credit on biologically fixed nitrogen, a rotation payment, or obligatory use of the Integrated Farm Management Program Option (IFMPO). However, elimination of the deficiency payment program would significantly reduce farm income. Modeling risk management and nitrate leaching dynamics are useful extensions of this research, as is estimating the benefits from averting nitrate leaching.

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Armour, R. J., and M. F. Vlljoen. "The leaching paradox and return flow management options for sustainable irrigated agriculture." South African Journal of Economic and Management Sciences 5, no. 2 (June 30, 2002): 430–51. http://dx.doi.org/10.4102/sajems.v5i2.2684.

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Leaching is necessary to maintain an acceptable salt balance in the root-zone of irrigated crops. This however contributes to point and non-point source water pollution externalities if not managed correctly. The use of a linear programming model, SALMOD (Salinity and Leaching Model for Optimal Irrigation Development) is demonstrated to determine the feasibility of leaching. artificial drainage, and on-farm storage/evaporation ponds to manage degraded return flows entering the water source and groundwater. Results show optimal cropping compositions and management practices to maximise farm returns subject to water quality conditions and return flow constraints. The economic effects of constraining return-flows and of water pricing policy on the volume of return flows are also determined. Results show valuable policy information regarding the interactions between artificial drainage subsidisation, return flow restrictions and on-farm storage.

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Aslan, Bulut, and A. Yonca Demir. "Organic Farming Suffices to Feed a Country: a Large-Scale Linear Programming Model to Develop an Organic Agriculture Plan for Turkey." Sustainable Agriculture Research 7, no. 1 (January 5, 2018): 118. http://dx.doi.org/10.5539/sar.v7n1p118.

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A frequently voiced critique is that due to lower yields on organically managed farmlands, one cannot feed a country using organic agriculture. In this paper, we aim to mathematically disprove this claim by developing a linear programming model and produce a detailed agriculture plan for Turkey sufficient to feed her population with a 2400 kcal daily menu on average, solely comprising of organic foods. The model uses information about population sizes and food needs of 81 cities in Turkey, and yields of 120 food, feed, forage crops, and four animal products. Intensive and extensive livestock production methods as well as food transportation between cities has been incorporated into the model. The resulting problem with 950 thousand variables and 40 thousand constraints can be solved with an optimization package in under a minute. Results, prescribing how many acres of each crop should be grown in each city, indicate that to feed the country fully on organic produce, 63% of the arable land suffices, yielding 8.9 million hectares of unused land where further organic foods could be grown for export or aid. We also run the model under different scenarios: fully vegetarian diet, omnivore model, different transportation structures, drought conditions and a limit on fruit trees. With this work, we have shown that it is possible to feed the whole population of Turkey with an agricultural practice that is not harmful to human health, soil, water and air; respects biological cycles and reduces food miles and fossil fuel consumption, thus contributing to sustainability and fighting climate change. We tested preliminary scenarios to understand the robustness of organic agriculture in the face of extreme weather events. The proposed model can also be applied to other countries when appropriate data are used.

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R, Shreedhar. "Multi Crop Optimization Using Linear Programming Model for Maximum Net Benefit." International Journal of Engineering & Technology 7, no. 3.12 (July 20, 2018): 797. http://dx.doi.org/10.14419/ijet.v7i3.12.16504.

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The water used for agriculture is 70% globally. This has resulted in new methods of saving water. Hence water saving techniques has to be practiced. In water resources planning and management, optimization techniques is used for limited use of resources such as such as water, land, production cost, manpower, fertilizers, seeds, and pesticides. For cultivating each crop, the land area needs to be planned properly. Hence the crop pattern has to be decided optimally depending on available water resources and on economic basis. Therefore farmer needs to be educated to adopt optimum cropping pattern which maximises the economic returns. Hence the study is taken up to optimize the allocation of land areas to crops. The objective function for multi crop model were formulated using linear programming for maximizing the net benefits. The study resulted in optimal cropping pattern for different water availabilities ranging from 2000 Ha-m to 5500 Ha-m. The maximum net benefit for the study area varied from Rs. 53.2 Crores for 2000 Ha-m water availability to Rs.78 Crores at 5000 Ha-m water availability.

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Garcia, Mauro Brino, and Lucas Rezende Gomide. "Use of linear programming models in experimentation with plant nutrients." CERNE 19, no. 2 (June 2013): 255–61. http://dx.doi.org/10.1590/s0104-77602013000200009.

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Nutrition is an important issue of plant cultivation and experimentation with plant nutrients is a supporting tool for agriculture. However, use of high purity grade reagents as nutrient sources can be expensive and increases the cost of an experiment. The objective of this study was to minimize the acquisition cost of high purity grade reagents in experiments on plant nutrient deficiency by using the missing element technique through linear programming models, and to generate recommendation tables for preparation of culture solutions, as well as to quantify gains through a simulated experiment. Two linear programming models were formulated containing concentration constraints for each nutrient in the culture solution. Model A was based on 16 reagents for preparation of the culture solution, while model B was based on 27 reagents, looking to increase choice options. Results showed that both models minimized the acquisition cost of reagents, allowing a 9.03% reduction in model A and a 25.98% reduction in model B. The missing sulfur treatment proved the most costly for reagent acquisition while the missing nitrogen treatment proved the least costly. It was concluded that the formulated models were capable of reducing acquisition costs of reagents, yet the recommendations generated by them should be tested and checked for practical viability.

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Vassalos, Michael, Carl R. Dillon, David Freshwater, and Pavlos Karanikolas. "Modeling multifunctionality of agriculture at a farm-level: The case of kerkini district, Northern Greece." Applied Studies in Agribusiness and Commerce 4, no. 3-4 (October 30, 2010): 59–64. http://dx.doi.org/10.19041/apstract/2010/3-4/9.

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Multifuncionality has become a central concern at both conceptual and empirical levels. In this study, a comparative evaluation of the economic performance of conventional and multifunctional farms (mainly organic farms) was conducted for the Lake Kerkini region (North Greece) with the use of mixed integer non-linear programming method. The economic performance of farms was evaluated in terms of farm income, resource allocation, production level and production mix. The results indicate that multifunctional farms have overall better economic performance and young farm managers are keener to adopt multifunctional farming than the older ones. Differences between the model results and the observed facts are attributed to the structural characteristics of the farms, along with the CAP measures and the existence of multiple objectives, beyond maximization of net farm returns.

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Altukhiov, A. I. "Methodological Provisions of Modeling Spatial Development of Agriculture in Russia: Undeservedly Forgotten, but Still in Demand." Economy of agricultural and processing enterprises, no. 7 (2020): 2–8. http://dx.doi.org/10.31442/0235-2494-2020-0-7-2-8.

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One of the main drawbacks of the existing economic and mathematical models of the spatial organization of agriculture in the country is the relatively weak relationship between the development, placement and specialization of its individual sub-sectors. Therefore, the results of their application do not always adequately reflect the spatial development of agriculture in the regions of the country. A model with a block-diagonal matrix structure, developed and success-fully tested in the 80s of the last century, was largely devoid of these shortcomings. Despite the fact that she was intended for a planned economy, many of the proposed methodological provi-sions in solving the task of optimizing the development, rational placement and deepening of agricultural specialization in the country have not lost their scientific and practical significance. So, in the process of developing and solving the problem, methods of mathematical statistics, linear programming and traditional methods of economic analysis were organically combined, and when substantiating various options for the spatial development of agriculture, methods of multi-criteria optimization were used. Particular attention was paid to the preparation of baseline information, a business case, the use of advanced technologies, the rational use of production resources, which made it possible to identify the bottlenecks in the spatial organization of agri-culture and propose optimal solutions.

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Chen, Hsiao Wei, and Yen Lan Liu. "Discussions on Eco-Economic Decision-Making in Farmland Management." Advanced Materials Research 807-809 (September 2013): 741–45. http://dx.doi.org/10.4028/www.scientific.net/amr.807-809.741.

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This paper examines the possibility of green fertilizer fallowing supporting eco (logical)-economicdecision-making in farmland management. Using scenario analysis and linear programming as research methods, this paper examines farmland allocations and fertilizer use in Taiwan under different economics perspectives and fallow subsidy rates. It is concluded that in agriculture development, reconciliation between the pursuit of profit and environmental sustainability is possible. However, it is not suggested that this reconciliation be achieved via high-level fallow subsidies. Rather, it is critical that the ecological economics view of decision-making be employed in farmland management.

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Campbell, J. C., J. Radke, J. T. Gless, and R. M. Wirtshafter. "An Application of Linear Programming and Geographic Information Systems: Cropland Allocation in Antigua." Environment and Planning A: Economy and Space 24, no. 4 (April 1992): 535–49. http://dx.doi.org/10.1068/a240535.

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This paper is focused on the application of linear programming (LP) in combination with a geographic information system (GIS) in planning agricultural land-use strategies. One of the essential inputs for planning any agricultural land-use strategy is a knowledge of the natural resources. This is even more critical in small countries such as those in the Eastern Caribbean, where land-area limitations dictate a greater need for careful assessment and management of these resources. The first step of the proposed methodology is to obtain an assessment of the natural resources available to agriculture. The GIS is used to delineate land-use conflicts and provide reliable information on the natural-resource database. This is followed by combining the data on natural resources with other quantifiable information on available labour, market forecasts, technology, and cost information in order to estimate the economic potential of the agricultural sector. LP is used in this step. Finally, the GIS is applied again to map the crop and land-allocation patterns generated by the LP model. The results are concrete suggestions for resource allocation, farm-size mix, policy application, and implementation projects.

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Latinopoulos, D. "Derivation of irrigation water demand functions through linear and non-linear optimisation models: application to an intensively irrigated area in northern Greece." Water Supply 5, no. 6 (December 1, 2005): 75–84. http://dx.doi.org/10.2166/ws.2005.0052.

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The growing need for sustainable management of water resources has introduced the implementation of water pricing as an indirect method for efficient and sustainable water use. Agriculture is the main consumer of water worldwide but in many countries it is also a very fragile socioeconomic sector. Within this sense, the paper examines the effect of irrigation water pricing on water demand and on farmers' income. The derivation of a demand function through a linear programming model is the most common approach as it is relatively easy to be implemented and has limited data requirements. However, this method does not allow for a possible reduction of water consumption from the maximum level of water productivity in order to attain the maximum economic outcome. Thus, a non-linear model was formulated in order to estimate the best allocation of water and land resources for each crop. The results show significant differences between the two models (the linear and the non-linear), especially at high water prices.

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Molla, Md Hasib Uddin, and Md Ainul Islam. "A Modified Filtering Technique for Efficient Extreme Points and Application of MOLP in Agriculture Sector in Bangladesh." Dhaka University Journal of Science 64, no. 2 (July 31, 2016): 147–52. http://dx.doi.org/10.3329/dujs.v64i2.54495.

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Multi-objective simplex algorithm computes all efficient extreme points of a multi-objective linear programming (MOLP) problem. For MOLP problem with large number of efficient extreme points, a filtering technique is necessary to present a small representative part of efficient extreme points. For this, we propose a filtering technique among efficient extreme points. In modern agriculture, we have to consider series of conflicting optimization criteria. For this reason, optimal cropping pattern, that is, allocation of land to various crops by making use of limited resources has become major challenges to get optimum return. To overcome this challenge, we illustrate the application of MOLP through a real life oriented problem of agricultural sector of Bangladesh. We also solve this problem by a self developed computer software which is based on multi-objective simplex algorithm and our proposed filtering technique. Dhaka Univ. J. Sci. 64(2): 147-152, 2016 (July)

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Veintimilla-Reyes, Jaime, Annelies De Meyer, Dirk Cattrysse, and Jos Van Orshoven. "A linear programming approach to optimise the management of water in dammed river systems for meeting demands and preventing floods." Water Supply 18, no. 2 (July 19, 2017): 713–22. http://dx.doi.org/10.2166/ws.2017.144.

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Abstract Water in sufficient quantity and quality is indispensable for multiple purposes like domestic and industrial use, irrigated agriculture, hydropower generation and ecosystem functioning. In many regions of the world, water availability is limited and even declining. Moreover, water availability is variable in space and time and often does not match with the spatio-temporal demand pattern. To overcome the temporal discrepancy between availability and consumption, reservoirs are constructed. Monitoring and predicting the water available in the reservoirs, the needs of the consumers and the losses throughout the river and water distribution system are necessary requirements to fairly allocate the available water to the different users, prevent floods and ensure sufficient water flow in the river. In this paper, this surface water allocation problem is considered a Network Flow Optimisation Problem (NFOP) solved by spatio-temporal optimisation using linear programming techniques.

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Ivanyo, Yaroslav, Sofia Petrova, Margarita Barsukova, and Gantulga Gombo. "Models of optimization of combination of production of agrarian products and harvesting of wild food resources." E3S Web of Conferences 222 (2020): 01016. http://dx.doi.org/10.1051/e3sconf/202022201016.

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The article is devoted to the results of modeling the combination of agricultural production and harvesting of wild food resources. Agricultural enterprise models that are able to expand food production activities through the use of wild plants are proposed. A prerequisite for the application of the developed linear programming models with uncertain parameters is the availability of sufficient reserves of wild food resources located at relatively small distances from the farm. This condition is acceptable for many farms in the Irkutsk region. As optimization problems, linear parametric problems with interval and random estimates are used. With sustainable agriculture, the uncertain values are yield, labor costs and prices for harvesting and selling wild plants. The models used to manage the activities of agricultural producers of the Irkutsk region showed additional opportunities for the development of the regional agro-industrial complex.

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Lovatto, Juliano, Rodrigo C. Santos, Cristiano M. A. de Souza, Rafael Zucca, Felipo Lovatto, and Luciano O. Geisenhoff. "Use of linear programming for decision making: An analysis of cost, time and comfort of rural housing dwellings." Revista Brasileira de Engenharia Agrícola e Ambiental 24, no. 9 (September 2020): 622–29. http://dx.doi.org/10.1590/1807-1929/agriambi.v24n9p622-629.

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ABSTRACT Brazilian agriculture production requires new types of rural buildings that are more sustainable, economical, and well adapted to their environment. Furthermore, these buildings are no longer simple living quarters, but a way of valuing rural workers. Thus, this study aimed to create a linear programming model for optimizing decision-making when different techniques and construction materials are combined to build rural housing dwellings, thereby enabling an assessment of both the cost and comfort of such buildings. The research considered localizing network facilities via analogies in order to adapt a budget matrix. Three main criteria were applied: cost, runtime, and the environmental comfort provided. The model comprised six construction systems, three types of sealing masonry, two types of roofing, and four types of tiles. Simulations were performed for two Brazilian states, considering the same reference date of validation and comparison. Each input variable resulted in a different construction model. It was demonstrated that the new industrialized construction technologies are advantageous since they provide faster execution, competitive prices, and sustainable raw materials, whilst the application of the criteria to the traditional system of reinforced concrete is also feasible. The linear programming model offers its users an additional decision-making tool for construction systems, enabling time and resource optimization.

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Kocjančič, Tina, Jaka Žgajnar, and Luka Juvančič. "Multiple-perspective Reorganisation of the Dairy sector: Mathematical Programming Approach." Business Systems Research Journal 7, no. 2 (September 1, 2016): 35–48. http://dx.doi.org/10.1515/bsrj-2016-0011.

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Abstract Background: Agriculture is a production system in which the economic principles of organisation act in mutual dependence with its ecological boundaries. Objectives: Building on this premise, the paper evaluates performance of a chosen agricultural production system (dairy production in Slovenia) from two complementary perspectives, the socio-economic and the biophysical. Methods/Approach: The latter is presented by means of emergy analysis, which is a system-based approach that measures the aggregate work of biosphere needed for the provision of goods or services in the units of solar energy joules. The novelty aspect of this paper is the introduction of emergy indicators into the standard socioeconomic optimisation model of the chosen agricultural production system. The optimisation model based on linear mathematical programming is designed to empirically investigate different alternatives to the sector’s reorganisation. Results: The results of the optimisation models suggest considerable restructuring of the sector and, consequently, large discrepancies in the sector’s performance. Conclusions: The results suggest that further expansion of organic production systems as a result of a stronger environmental focus in farm management would improve the sector from both, the socio-economic and the emergy perspective. Moreover, even pursuing certain socio-economic targets may improve the sector’s biophysical performance and lower pressure on the local environment.

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Bazzani, Guido M., Giuliano Vitali, Concetta Cardillo, and Maurizio Canavari. "Using FADN Data to Estimate CO2 Abatement Costs from Italian Arable Crops." Sustainability 13, no. 9 (May 4, 2021): 5148. http://dx.doi.org/10.3390/su13095148.

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The assessment of economic and environmental sustainability of agricultural systems represents a critical issue, which has been addressed in this work with a multi-objective programming model to explore the abatement costs (AC) of CO2 for a set of representative contexts of Italian arable land agriculture. The study was based on the FADN-compliant Italian database RICA and estimates the abatement costs of CO2 emissions in a short time horizon, using linear multi-objective programming and compromise programming. RICA data were used to quantify technical parameters of the model, adopting an innovative concept of a cropping scheme to simulate land-use adaptation. The study shows a quite diversified situation regarding income and emission levels per hectare across the Italian region and farm classes. A reduction of CO2 emissions higher than 5 kg/ha at an AC lower than 1 EUR/kg is affordable only in seven regions, among which Abruzzo, Lombardy, and Puglia show the highest potential. Comparing the estimated abatement costs for CO2 emissions with the corresponding European Trade System prices highlights a difference of 1 order of magnitude, proving that emission reductions for Italian arable crops still require research and innovation to lower adaptation costs.

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Yulianto, Irfan, Budy Wiryawan, and Am Azbas Taurusman. "ECOSYSTEM APPROACH TO REEF FISHERIES MANAGEMENT IN WEH ISLAND, NANGROE ACEH DARUSSALAM." Indonesian Fisheries Research Journal 17, no. 2 (February 9, 2017): 53. http://dx.doi.org/10.15578/ifrj.17.2.2011.53-61.

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Fisheries management has been traditionally governed to maximize economic benefit with little concern on its ecological impacts. Food and Agriculture Organization with its Code of Conduct for Responsible Fisheries has played an important role to a fundamental change in the new paradigm of fisheries management, which include ecosystem aspect. The Food and Agriculture Organization has mandated that every country in the world should use this approach. Weh Island is located in AcehProvince that has good coral reef condition and rich in reef fishes, therefore reef fishery is prominent. The objectives of this study are (1) to study the ecological status of reef fish, and (2) to formulate the priority areas as candidates of marine protected areas in Weh Island. Fish catch survey, underwater visual census, and focus group discussion were conducted to collect data. Data analysis used fish biomass, financial analysis, linear goal programming, and marxan analysis. Results of this study successfully identified eight fishing gears operated in Weh Island in artisanal reef fisheries. These fishing gears are gillnet, bottom gillnet, handline, muroami, trolline, speargun, longline, and purseseine. There were 84 species identified as high economic value species and were modelled in this study. Gillnet and bottom gillnet were identified as optimum fishing gears. I.e. Meulee, Anoi Itam, Iboih, Jaboi, and Klah Island were identified as priority areas.

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Beula, D. Hebsiba, S. Srinivasan, and C. D. Nanda Kumar. "Crop Insurance Prediction Using R for Pradhan Mantri Fasal Bima Yojana in TamilNadu." International Journal of Risk and Contingency Management 10, no. 4 (October 2021): 46–57. http://dx.doi.org/10.4018/ijrcm.2021100104.

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Agriculture is the primary source of livelihood for farmers in many underdeveloped regions, so due to climate change or other risks, crop insurance is thought to be essential, but the research question answered in the current study pertains to insurance program performance. The government-administered crop insurance program was analysed using a mixed methods design. A multiple case study was conducted in the TamilNadu region (India) to analyse the program, identify the causal factors, and collect relevant claim secondary data. Then the R statistical program was applied to analyse crop performance by developing a linear model of crop actual yields versus threshold yields (rabi, paddy, and kharif) using claim payments as the dependent variable. R statistical regression model programming was explained in detail. Recommendations were provided to economic decision makers on how to enhance agricultural insurance and rural development.

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Behera, U. K., H. Kaechele, and J. France. "Integrated animal and cropping systems in single and multi-objective frameworks for enhancing the livelihood security of farmers and agricultural sustainability in Northern India." Animal Production Science 55, no. 10 (2015): 1338. http://dx.doi.org/10.1071/an14526.

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Fast degrading and declining land, water availability, biodiversity, environment and other natural resources, together with shrinking farm returns and reduced crop productivity caused by continuous and intensive cultivation of rice-wheat systems, necessitate diversification of farming in Northern India. Integrated farming systems (IFS) involving animals (livestock, fish, etc.) and cropping (cereals, trees, etc.) are recognised as an alternative for preserving ecosystems and enhancing livelihood security. A study was therefore undertaken under Northern Indian conditions to develop IFS models for various sizes of farm and to compare these models with the existing rice-wheat system for sustainability and profitability. The IFS models were developed in single objective (using linear programming) and multi-objective (using compromise programming) frameworks. Multi-objective analysis provides deeper insight into the problem as it caters directly for the multi-faceted needs of the farmers. These parallel methodologies offer a novel approach to modelling IFS to draw different farming scenarios for comparison. The IFS strategies developed show the potential to generate a greater farm income than with existing rice-wheat cropping for all sizes of farm. The study revealed that IFS offer more perspectives for an economically viable and sustainable agriculture for typical farms in Northern India.

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Hu, Zhong Ke, Chao Liu, Wen Hua Zhuang, Tie Gang Liu, and Zhuo Li. "Optimization of Multi-Objective Crop Pattern Based on Water and Fertilizer Resources Allocation." Applied Mechanics and Materials 522-524 (February 2014): 1034–38. http://dx.doi.org/10.4028/www.scientific.net/amm.522-524.1034.

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To enhance the utilization efficiency of water and fertilizer resources, and improve agricultural ecological environment in resettlement area, a crop planting structure optimization model was established by the use of multiple objective linear programming (MOLP) method, and solved by two-phase algorithm. In this model, multiple targets, such as the economic, social and ecological benefits of this region were taken into account. The results showed that the MOLP model and its solution were feasible and practical. The optimized area of rice, corn and tobacco reduced by 16%, 100% and 76% respectively, and the optimized area of wheat and sugarcane increased by 82% and 78% compared with the current planting area. And the net economic and social benefits increased by 4% and 62%. The optimization scheme played a guiding role in the adjustment of agricultural structure, and promoted the sustainable development of agriculture in resettlement area.

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Nijnik, Maria, Arie Oskam, and Anatoliy Nijnik. "Afforestation for the Provision of Multiple Ecosystem Services: A Ukrainian Case Study." International Journal of Forestry Research 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/295414.

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This paper presents an economic analysis of the planting of trees on marginal lands in Ukraine for timber production, erosion prevention, and climate mitigation. A methodology combining econometric analysis, simulation modelling, and linear programming to analyse the costs and benefits of such afforestation has been adopted. The research reveals that, at discount rates lower than 2%, establishment of new forests is economically justified in the majority of forestry zones. Incorporating the effects of afforestation on mitigating climate change increases social benefits. However, the results indicate that whilst soil protection benefits to agriculture from afforestation in the Steppe are expected to be high, carbon sequestration and timber production activities in the Steppe are cost inefficient due to low rates of tree growth and relatively high opportunity costs of land. The opportunity costs of land are also high in the Polissja where afforestation is cost inefficient at 2% and higher discount rates.

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Yates, C. M., and T. Rehman. "Integration of Markov and Linear Programming Models to Assess the Farmgate and National Consequences of Adopting New Bovine Reproductive Technologies in the United Kingdom Agriculture." Journal of the Operational Research Society 47, no. 11 (November 1996): 1327. http://dx.doi.org/10.2307/3010199.

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Yates, C. M., and T. Rehman. "Integration of Markov and Linear Programming Models to Assess the Farmgate and National Consequences of Adopting New Bovine Reproductive Technologies in the United Kingdom Agriculture." Journal of the Operational Research Society 47, no. 11 (November 1996): 1327–42. http://dx.doi.org/10.1057/jors.1996.169.

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Bartolini, F., G. M. Bazzani, V. Gallerani, M. Raggi, and D. Viaggi. "The impact of water and agriculture policy scenarios on irrigated farming systems in Italy: An analysis based on farm level multi-attribute linear programming models." Agricultural Systems 93, no. 1-3 (March 2007): 90–114. http://dx.doi.org/10.1016/j.agsy.2006.04.006.

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Journal articles on the topic 'Agriculture Linear programming. Agriculture Terrains'

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